With streamlined access to petabytes of science-ready geospatial data and the computing power to go with it, the Applied Science team at Descartes Labs is building a digital twin of the earth. We model our planet by combining sensor data with a mix of physical, statistical, and machine learning modeling approaches.
We’re looking for agronomists to apply this data and computing power towards interesting agricultural applications on a global scale.
- Use our archive of satellite imagery, weather data, and other geospatial datasets to model agricultural crops around the world (crop identification, crop yield, etc.)
- Design, build, test, and validate models within a cloud-based environment
- Work with clients to provide meaningful scientific analysis for a variety of stakeholders
- Interact with clients to brainstorm methodologies and present results
- Work with our engineering team to continuously improve our platform
Required Skills and Experience
- Bachelor’s degree in a relevant scientific field (e.g. agronomy, agricultural sciences, biostatistics, earth sciences)
- Strong statistical background
- Experience with spatial data
- Demonstrated proficiency in a scientific programming language (preferably Python)
- Strong written and verbal communication skills
- Self-motivated and able to work independently
- Advanced degree (MS/PhD) in a relevant field
- Image processing experience
- Experience with remote sensing
- Experience with numpy, sklearn, scikit-image
- Peer-reviewed published journal articles on related topics
- Experience with version control software (e.g. GitHub, Mercurial, Subversion, etc.)
- Experience with cloud and/or distributed computing
To apply for this job please visit jobs.lever.co.